A big part of his work is figuring out when a statistical method is truly the best choice. Some problems have straightforward ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

With AI Software Integrity Builder, Keysight empowers engineering teams to move from fragmented testing to a unified AI ...

There is often a disconnect between the intended functionality of an artificial intelligence model and its actual functionality once it's integrated into healthcare workflows. Epic has developed an ...

We collaborate with the world's leading lawyers to deliver news tailored for you. Sign Up for any (or all) of our 25+ Newsletters. Some states have laws and ethical rules regarding solicitation and ...

CU Boulder researchers apply machine learning to snow hydrology in Colorado mountain drainage basins, finding a new way to accurately predict the availability of water Determining how much water is ...

Real world analysis of VTE incidence in lung cancer: A comprehensive assessment of the Khorana score and other clinical factors in predicting VTE incidence. This is an ASCO Meeting Abstract from the ...

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...

Supervised learning allows broad-scale mapping of variables measured at discrete points in space and time, e.g., by combining satellite and in situ data. However, it can fail to make accurate ...